The estimation of the postmortem interval (PMI) remains one of the most significant challenges in forensic science. Traditional methods, while foundational, are often limited by environmental factors and a narrow effective time frame. The emergence of high-throughput sequencing technologies has opened a new frontier in forensic investigation through the study of the thanatomicrobiome the microbial communities that colonize a body after death. This review provides a comprehensive overview of the current state of research on the forensic microbiome and its application in PMI estimation. We examine the key methodologies, including 16S rRNA sequencing and shotgun metagenomics, and the application of machine learning algorithms such as Random Forest models, which have demonstrated remarkable accuracy in predicting PMI. The review synthesizes findings from key studies, highlighting the predictable, time-dependent succession of microbial communities in various body sites and environments. We also discuss the significant challenges, including the lack of standardized protocols and the influence of environmental variables, that must be addressed for this technology to be fully integrated into forensic practice. Finally, we outline future directions for research, emphasizing the need for large-scale validation studies and the development of integrated, multi-omic approaches to enhance the precision and reliability of microbial-based PMI estimation.